Data Science with Llms: Analyzing Text, Tables, Images and Sound
暫譯: 使用大型語言模型的資料科學:分析文本、表格、圖像和聲音
Trummer, Immanuel
- 出版商: Manning
- 出版日期: 2025-05-20
- 售價: $1,590
- 貴賓價: 9.5 折 $1,511
- 語言: 英文
- 頁數: 256
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1633437647
- ISBN-13: 9781633437647
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相關分類:
LangChain、Data Science
尚未上市,無法訂購
相關主題
商品描述
Speed up common data science tasks with AI assistants like ChatGPT and Large Language Models (LLMs) from Anthropic, Cohere, AI21, Hugging Face, and more! Using ChatGPT and other AI-powered tools, you can analyze almost any kind of data with just a few short lines of plain English. In Data Science with LLMs, you'll learn important techniques for streamlining your data science practice, expanding your skillset and saving you hours--or even days--of time. Inside, you'll learn how to use AI assistants to: - Analyze text, tables, images, and audio files
- Extract information from multi-modal data lakes
- Classify, cluster, transform, and query multimodal data
- Build natural language query interfaces over structured data sources
- Use LangChain to build complex data analysis pipelines
- Prompt engineering and model configuration This practical book takes you from your first prompts through advanced techniques like building automated analysis pipelines and fine-tuning existing models. You'll learn how to create meaningful reports, generate informative graphs, and much more. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the book Data Science with LLMs teaches you to use a new generation of AI assistants and Large Language Models (LLMs) to simplify and accelerate common data science tasks. Cornell professor and long-time LLM advocate Immanuel Trummer reveals techniques he's pioneered for getting the most out of LLMs in data science, including model selection and specialization, techniques for tuning parameters, and reliable prompt templates. You'll start with an in-depth exploration of how LLMs work. Then, you'll dive into no-code data analysis with LLMs, creating custom operators with the OpenAI Python API, and building complex data analysis pipelines with the cutting edge LangChain framework. About the reader For data scientists, data analysts, and others who are interested in making their work easier through the use of artificial intelligence techniques. Readers should have a basic understanding of the Python programming language. About the author Immanuel Trummer is an assistant professor for computer science at Cornell University and leader of the Cornell Database Group. His papers have been selected for "Best of VLDB", "Best of SIGMOD", for the ACM SIGMOD Research Highlight Award, and for publication in CACM as CACM Research Highlight. Immanuel's online course on data management has reached over a million views on YouTube. Over the past few years, his group has published extensively on projects that apply large language models in the context of data science.
- Extract information from multi-modal data lakes
- Classify, cluster, transform, and query multimodal data
- Build natural language query interfaces over structured data sources
- Use LangChain to build complex data analysis pipelines
- Prompt engineering and model configuration This practical book takes you from your first prompts through advanced techniques like building automated analysis pipelines and fine-tuning existing models. You'll learn how to create meaningful reports, generate informative graphs, and much more. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the book Data Science with LLMs teaches you to use a new generation of AI assistants and Large Language Models (LLMs) to simplify and accelerate common data science tasks. Cornell professor and long-time LLM advocate Immanuel Trummer reveals techniques he's pioneered for getting the most out of LLMs in data science, including model selection and specialization, techniques for tuning parameters, and reliable prompt templates. You'll start with an in-depth exploration of how LLMs work. Then, you'll dive into no-code data analysis with LLMs, creating custom operators with the OpenAI Python API, and building complex data analysis pipelines with the cutting edge LangChain framework. About the reader For data scientists, data analysts, and others who are interested in making their work easier through the use of artificial intelligence techniques. Readers should have a basic understanding of the Python programming language. About the author Immanuel Trummer is an assistant professor for computer science at Cornell University and leader of the Cornell Database Group. His papers have been selected for "Best of VLDB", "Best of SIGMOD", for the ACM SIGMOD Research Highlight Award, and for publication in CACM as CACM Research Highlight. Immanuel's online course on data management has reached over a million views on YouTube. Over the past few years, his group has published extensively on projects that apply large language models in the context of data science.
商品描述(中文翻譯)
利用像 ChatGPT 和 Anthropic、Cohere、AI21、Hugging Face 等公司的大型語言模型 (LLMs) 加速常見的資料科學任務!
使用 ChatGPT 和其他 AI 驅動的工具,您可以用幾行簡單的英文分析幾乎任何類型的數據。在 使用 LLMs 的資料科學 一書中,您將學習到簡化資料科學實踐的重要技術,擴展您的技能組合,並節省數小時甚至數天的時間。 在書中,您將學會如何使用 AI 助手來: - 分析文本、表格、圖像和音頻文件- 從多模態數據湖中提取信息
- 對多模態數據進行分類、聚類、轉換和查詢
- 在結構化數據源上構建自然語言查詢介面
- 使用 LangChain 構建複雜的數據分析管道
- 提示工程和模型配置 這本實用的書籍將帶您從第一個提示開始,學習到像構建自動化分析管道和微調現有模型等高級技術。您將學會如何創建有意義的報告、生成信息豐富的圖表等等。 購買印刷版書籍可獲得 Manning Publications 提供的免費 PDF 和 ePub 格式電子書。 關於本書 《使用 LLMs 的資料科學》教您如何使用新一代 AI 助手和大型語言模型 (LLMs) 來簡化和加速常見的資料科學任務。康奈爾大學教授及長期 LLM 擁護者 Immanuel Trummer 揭示了他在資料科學中充分利用 LLMs 的技術,包括模型選擇和專業化、調整參數的技術以及可靠的提示模板。 您將從深入探索 LLMs 的工作原理開始。然後,您將深入了解無需編碼的 LLM 數據分析,使用 OpenAI Python API 創建自定義運算符,以及使用尖端的 LangChain 框架構建複雜的數據分析管道。 關於讀者 本書適合資料科學家、資料分析師及其他希望通過使用人工智慧技術來簡化工作的人士。讀者應具備基本的 Python 程式語言理解。 關於作者 Immanuel Trummer 是康奈爾大學計算機科學的助理教授,也是康奈爾數據庫小組的負責人。他的論文曾獲選為「最佳 VLDB」、「最佳 SIGMOD」,以及 ACM SIGMOD 研究亮點獎,並在 CACM 發表為 CACM 研究亮點。Immanuel 的數據管理在線課程在 YouTube 上的觀看次數已超過一百萬。在過去幾年中,他的小組在將大型語言模型應用於資料科學的項目上發表了大量研究。
作者簡介
Immanuel Trummer is an assistant professor for computer science at Cornell University and leader of the Cornell Database Group. His papers have been selected for "Best of VLDB", "Best of SIGMOD", for the ACM SIGMOD Research Highlight Award, and for publication in CACM as CACM Research Highlight. Immanuel's online course on data management has reached over a million views on YouTube. Over the past few years, his group has published extensively on projects that apply large language models in the context of data science.
作者簡介(中文翻譯)
伊曼紐爾·特魯默是康奈爾大學的計算機科學助理教授,也是康奈爾數據庫小組的負責人。他的論文曾獲選為「最佳 VLDB」、「最佳 SIGMOD」,以及 ACM SIGMOD 研究亮點獎,並在 CACM 發表為 CACM 研究亮點。伊曼紐爾的數據管理在線課程在 YouTube 上的觀看次數已超過一百萬。在過去幾年中,他的團隊在應用大型語言模型於數據科學的項目上發表了大量研究。